mtsdi: Multivariate time series data imputation

This is an EM algorithm based method for imputation of
missing values in multivariate normal time series. The
imputation algorithm accounts for both spatial and temporal
correlation structures. Temporal patterns can be modelled using
an ARIMA(p,d,q), optionally with seasonal components, a
non-parametric cubic spline or generalised additive models with
exogenous covariates. This algorithm is specially tailored for
climate data with missing measurements from several monitors
along a given region.